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Information Extraction of High-Resolution Remotely Sensed Image Based on Multiresolution Segmentation
The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of a remotely sensed image based on this principle. The target image was divided into regions based on object-oriented multiresolution segmentation and edge-detection. Furthermore, object hierarchy was created, and a series of features (water bodies, vegetation, roads, residential areas, bare land and other information) were extracted by the spectral and geometrical features. The results indicate that the edge-detection has a positive effect on multiresolution segmentation, and overall accuracy of information extraction reaches to 94.6% by the confusion matrix.
Information Extraction of High-Resolution Remotely Sensed Image Based on Multiresolution Segmentation
The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of a remotely sensed image based on this principle. The target image was divided into regions based on object-oriented multiresolution segmentation and edge-detection. Furthermore, object hierarchy was created, and a series of features (water bodies, vegetation, roads, residential areas, bare land and other information) were extracted by the spectral and geometrical features. The results indicate that the edge-detection has a positive effect on multiresolution segmentation, and overall accuracy of information extraction reaches to 94.6% by the confusion matrix.
Information Extraction of High-Resolution Remotely Sensed Image Based on Multiresolution Segmentation
Peng Shao (author) / Guodong Yang (author) / Xuefeng Niu (author) / Xuqing Zhang (author) / Fulei Zhan (author) / Tianqi Tang (author)
2014
Article (Journal)
Electronic Resource
Unknown
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